A Novel Approach for Enhancing Routing in Wireless Sensor Networks using ACO Algorithm

Wireless Sensors Network (WSN) is an emergent technology that aims to offer innovative capacities. In the last decade, the use of these networks increased in various fields like military, science, and health due to their fast and inexpressive deployment and installation. However, the limited sensor battery lifetime poses many technical challenges and affects essential services like routing. This issue is a hot topic of search, many researchers have proposed various routing protocols aimed at reducing the energy consumption in WSNs. The focus of this work is to investigate the effectiveness of integrating ACO algorithm with routing protocols in WSNs. Moreover, it presents a novel approach inspired by ant colony optimization (ACO) to be deployed as a new routing protocol that addresses key challenges in wireless sensor networks. The proposed protocol can significantly minimize nodes energy consumption, enhance the network lifetime, reduce latency, and expect performance in various scenarios

Fault-tolerant and QoS based Network Layer for Security Management

Wireless sensor networks have profound effects on many application fields like security management which need an immediate, fast and energy efficient route. In this paper, we define a fault-tolerant and QoS based network layer for security management of chemical products warehouse which can be classified as real-time and mission critical application. This application generate routine data packets and alert packets caused by unusual events which need a high reliability, short end to end delay and low packet loss rate constraints. After each node compute his hop count and build his neighbors table in the initialization phase, packets can be routed to the sink. We use FELGossiping protocol for routine data packets and node-disjoint multipath routing protocol for alert packets. Furthermore, we utilize the information gathering phase of FELGossiping to update the neighbors table and detect the failed nodes, and we adapt the network topology changes by rerun the initialization phase when chemical units were added or removed from the warehouse. Analysis shows that the network layer is energy efficient and can meet the QoS constraints of unusual events packets

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-to-performance ratios. A wide variety of machine learning models are proposed by researchers to perform this task, and most of them are either highly complex, or showcase low-levels of efficiency when applied to large-scale networks. To overcome these issues, this text proposes design of a Q-learning based iterative sleep-scheduling and fuses these schedules with an efficient hybrid bioinspired multipath routing model for large-scale multimedia network sets. The proposed model initially uses an iterative Q-Learning technique that analyzes energy consumption patterns of nodes, and incrementally modifies their sleep schedules. These sleep schedules are used by scalar nodes to efficiently wakeup multimedia nodes during adhoc communication requests. These communication requests are processed by a combination of Grey Wolf Optimizer (GWO) & Genetic Algorithm (GA) models, which assist in the identification of optimal paths. These paths are estimated via combined analysis of temporal throughput & packet delivery performance, with node-to-node distance & residual energy metrics. The GWO Model uses instantaneous node & network parameters, while the GA Model analyzes temporal metrics in order to identify optimal routing paths. Both these path sets are fused together via the Q-Learning mechanism, which assists in Iterative Adhoc Path Correction (IAPC), thereby improving the energy efficiency, while reducing communication delay via multipath analysis. Due to a fusion of these models, the proposed Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks (QIBMRMN) is able to reduce communication delay by 2.6%, reduce energy consumed during these communications by 14.0%, while improving throughput by 19.6% & packet delivery performance by 8.3% when compared with standard multimedia routing techniques

Optimized Forwarding for Wireless Sensor Networks by Fuzzy Inference System

For the flat wireless sensor networks, we investigate the optimization problem of the routing path based on the metrics: distance, power and link usage to maximize the lifetime of the sensor networks. We employ the well known fuzzy inference systems (FIS) for the selection of the best node, from the candidate nodes, in order to forward packet to the sink. Simulation results show that network lifetime can be improved by employing the optimized routing protocol

An Energy-Efficient Forwarding Scheme for Wireless Sensor Networks

Energy-efficient forwarding becomes important if resources and battery lifetime are limited such as in Wireless Sensor Networks. Although widely used, simple hop-based forwarding along a path from one node towards a sink can be very inefficient in terms of delivery rate as well as energy efficiency, especially in lossy environments. We will show that just minimizing the expected number of transmissions within the network is not always the most efficient forwarding strategy. Using a realistic link loss model, we derive two new forwarding schemes named Single-Link and Multi-Link Energy-Efficient Forwarding that trade off delivery rate and energy costs best by maximizing energy efficiency. Multi-Link Forwarding further benefits from addressing multiple receivers during packet forwarding, instead of a single one. By mathematical analyses, extensive simulations, and experimental experiments we contrast the performance of our approaches against a comprehensive framework of different forwarding strategies

Game theory based Ad-hoc On Demand Distance Vector Routing Protocol to Extend the Wireless Sensor Networks Life Time

This paper proposes a solution to increase the energy life time of wireless sensor networks (WSNs) via a concept of game theory enabled ad-hoc on demand distance vector (AODV) routing algorithm. Game theory is an optimal promising candidate for decision making in a wireless networking scenario to find the optimal path for data packets transfer between source node and destination node, where combination with the AODV routing algorithm, a procedure of game theory enabled AODV (GTEAODV) is developed and proposed in this research paper. The developed and proposed methodology is validated through simulation in NS2 environment and the results show an improvement in energy life time of the order of 30-35% in comparison to the existing routing methodology which uses co-operative routing techniques among the nodes in WSN. Further, the throughput of game theory enabled adhoc on demand routing is also highly improved in comparison to existing traditional approaches though obtained results. Though, game theory approach is an existing approach concatenation of it with AODV can provide increased network performance which is significant as portrayed in research results shown in the paper. Hence, by virtue of providing enhanced energy life time and data security through the nature of the algorithm, the proposed GTEAODV algorithm can be employed in defence applications for secure data transmission and reception for forthcoming deployment of 5G systems which are blossoming in world wide scenario

Acdmcp: An adaptive and completely distributed multi-hop clustering protocol for wireless sensor networks

Clustering is a very popular network structuring technique which mainly addresses the issue of scalability in large scale Wireless Sensor Networks. Additionally, it has been shown to improve the energy efficiency and prolong the life of the network. The suggested protocols mostly base their clustering criteria on some grouping attribute(s) of the nodes. One important attribute that is largely ignored by most of the existing multi-hop clustering protocols is the reliability of the communication links between the nodes. In this paper, we suggest an adaptive and completely distributed multi-hop clustering protocol that incorporates different notions of reliability of the communication links, among other things, into a composite metric and uses it in all phases of the clustering process. The joining criteria for the nodes, which lie at one hop from the elected cluster heads, to a particular cluster not only consider the reliability of their communication link with their cluster head but also other important attributes. The nodes that lie outside the communication range of cluster heads become cluster members transitively through existing cluster members utilizing the end-to-end notion of link reliability, between the nodes and the cluster heads, along with other important attributes. Similarly, inter-cluster communication paths are selected using a set of criteria that includes the end-to-end communication link reliability with the sink node along with other important node and network attributes. We believe that incorporating link reliability in all phases of clustering process results in an efficient multi-hop communication hierarchy that has the potential of bringing down the total communication costs in the network

Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues